Traditionally, to detect anomalous events that relate to the performance of a production system, engineers manually analyze log files of various data pertaining to the production system. This method of anomaly detection may be very time-consuming and error-prone. Furthermore, this method of anomaly detection may not allow for a real-time analysis and response to the problem causing the anomalous event.